Date: Wed, 3 Sep 2008 17:08:42 0400
ReplyTo: Sigurd Hermansen <HERMANS1@WESTAT.COM>
Sender: "SAS(r) Discussion" <SASL@LISTSERV.UGA.EDU>
From: Sigurd Hermansen <HERMANS1@WESTAT.COM>
Subject: Re: Class variables proc logistic
InReplyTo: <48BEF38D.40907@gmx.de>
ContentType: text/plain; charset="usascii"
Monika:
Neither alternative makes much of a difference. Stepwise variable selection methods have obvious drawbacks that make them dangerous (in that the results can be misleading) if not simply a waste of time and resources. David Cassell and Peter Flom have presented all the usual caveats on SASL and elsewhere. I'll present some examples of how stepwise selection goes wrong at SESUG 2008.
PROC GLMSELECT (LASSO) gives you a better chance of specifying a useful model. For that you need V9.2 or a download from the SAS Web site.
S
Original Message
From: SAS(r) Discussion [mailto:SASL@LISTSERV.UGA.EDU] On Behalf Of Monika Nauroth
Sent: Wednesday, September 03, 2008 4:29 PM
To: SASL@LISTSERV.UGA.EDU
Subject: Re: Class variables proc logistic
Does anyone know if the variable selection of a stepwise logistic regression depends on the choice of use of dummy coding or effect coding?
tal schrieb:
> On Sep 3, 3:05 am, peterflomconsult...@mindspring.com (Peter Flom)
> wrote:
>> tal <talila...@GMAIL.COM> wrote
>>
>>> I'm not sure but i don't think the sampling is stratified. i have ,
>>> lets say:20 variables "is XX important to you?" for each quest the
>>> response is
>>> 1 important 2 not important 3no answer.
>>> (When i use the class statement 3 dummy variables are created, but
>>> I'm only interested in the first two the third one is created
>>> automatically but i don't need it and that's where I have a
>>> problem) As i said , for each observation i want to count the number
>>> of missing values in the questionnaire and take it as explanatory
>>> variable but since a dummy variable is created for each var1var20
>>> the number of missing values is a linear combination of these. Does
>>> anybody know how to create only the 2 dummy variables that i need in
>>> proc logistic, and drop the third one?
>> If your IV has 3 levels, then LOGISTIC will create 2 dummy
>> variables;, by default SAS uses EFFECT coding, and dummy (or
>> reference) coding, is often better, but I don't think that explains
>> your problem
>>
>> So, could you show your code?
>>
>> e.g
>>
>> data today;
>> length IV $4;
>> input iv $ dv $ weight;
>> datalines;;
>> Imp yes 100
>> NotI yes 200
>> NA yes 50
>> Imp no 50
>> NotI no 100
>> NA no 50
>> ;;;;
>>
>> proc logistic data = today;
>> class iv (param = ref);
>> model dv = iv;
>> weight weight;
>> run;
>>
>> creates two dummy variables
>>
>> Peter
>>
>> Peter L. Flom, PhD
>> Statistical Consultant
>> www DOT peterflom DOT com
>
> Hi! I found another way to do it. Thanks a lot anyway!
>
